Discovering Generative Uncertainty in Learning Analytics Dashboards

Nguyen, Ha; Campos, Fabio; Ahn, June

doi:10.1007/978-3-030-81222-5_21

Cited by 5 publications

(6 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Considering that educators frequently experience uncertainty in their work (Munthe, 2003), we understand productive action as transforming instances of “not knowing” into patterns where educators formulate questions, engage in improvement conversations and devise next steps for instruction. In prior work, we find that occurrences of specific patterns—such as asking questions about the data coupled with data triangulation, information seeking, and pedagogical intentions when making sense of LA data visualizations—indicate GU (Nguyen et al, 2021). Such an interpretive stance opens avenues for productive data‐based inquiry and instructional improvement.…”

Section: Introductionmentioning

confidence: 78%

“…Through design narratives that capture the history and development of designed artefacts (Hoadley, 2002), we address the following research question: how-and to what extent-might cultural forms be leveraged in LA design? To answer this question, we examined the extent to which our tool supported educators to engage in what we call generative uncertainty (GU)-an interpretive stance in which educators develop productive inquiries towards data, as opposed to merely producing justifications for what is being displayed (Nguyen et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…The tool we designed throughout this work was intended to support what we termed Generative Uncertainty (GU), an analytical stance where educators work with the ambiguity of data and engage in practices that have the potential to lead to productive action from data (Nguyen et al, 2021). Considering that educators frequently experience uncertainty in their work (Munthe, 2003), we understand productive action as transforming instances of “not knowing” into patterns where educators formulate questions, engage in improvement conversations and devise next steps for instruction.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Leveraging cultural forms in human‐centred learning analytics design

Campos,

Nguyen,

Ahn

et al. 2023

Brit J Educational Tech

Self Cite

View full text Add to dashboard Cite

In this article, we offer theory‐grounded narratives of a 4‐year participatory design process of a Learning Analytics tool with K‐12 educators. We describe how we design‐in‐partnership by leveraging educators' routines, values and cultural representations into the designs of digital dashboards. We make our long‐term reasoning visible by reflecting upon how design decisions were made, discussing key tensions and analysing to what extent the developed tools were taken up in practice. Through thick design narratives, we reflect upon how cultural forms—recognizable cultural constructs that might cue and facilitate specific activities—were identified among educators and informed the design of a dashboard. We then examined the extent to which the designed tool supported coaches and teachers to engage in Generative Uncertainty, an interpretive stance in which educators manifest productive inquiries towards data. Our analysis highlights that attuning to cultural forms is a valuable first step but not enough towards designing LA tools for systems in ways that fit institutionalized practices, challenge instrumental uses and spur productive inquiry. We conclude by offering two key criteria for making culturally‐grounded design decisions in the context of long‐term partnerships. Practitioner notesWhat is already known about this topic Participatory design can invite stakeholders to directly inform the creation of LA artefacts that fit their needs, context and cultural markers. What this paper adds Cultural forms can be identified and leveraged in the design of LA tools. HCLA scholars ought to design for systems—the complex body of organizational routines, cultural practices and interactions among multiple stakeholders—and not just for users. Implications for practice and/or policy Leveraging cultural forms in LA needs to be accompanied by a critical view of which practices, behaviours, values and structures are suggested by such forms. Designing features that are easy to use, are associated with concrete tasks, and fit into existing cultural practices are three criteria for embedding cultural forms into LA design.

show abstract

Section: Introductionmentioning

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Leveraging cultural forms in human‐centred learning analytics design

Campos,

Nguyen,

Ahn

et al. 2023

Brit J Educational Tech

Self Cite

View full text Add to dashboard Cite

show abstract

“…Here, the AI system (and student) can reach a point of "not knowing", signaling limits of knowledge and unknowns within a given context. For example, "intelligent tutorial systems" are being designed with two (rather than one) pedagogical agents that sometimes disagree with one another (Nguyen et al, 2021). Students interacting with such systems are thereby TA B L E 1 A summary of tensions between artificial intelligence (AI) features and the risks to consider when integrating AI into anatomy education forced to think about how to manage this uncertainty stimulated by this conflict.…”

Section: Tension #1: Artificial Intelligence Education and The Uncert...mentioning

confidence: 99%

Artificial intelligence and clinical anatomical education: Promises and perils

Lazarus

Truong

Douglas

et al. 2022

Anatomical Sciences Ed

View full text Add to dashboard Cite

Anatomy educators are often at the forefront of adopting innovative and advanced technologies for teaching, such as artificial intelligence (AI). While AI offers potential new opportunities for anatomical education, hard lessons learned from the deployment of AI tools in other domains (e.g., criminal justice, healthcare, and finance) suggest that these opportunities are likely to be tempered by disadvantages for at least some learners and within certain educational contexts. From the perspectives of an anatomy educator, public health researcher, medical ethicist, and an educational technology expert, this article examines five tensions between the promises and the perils of integrating AI into anatomy education. These tensions highlight the ways in which AI is currently ill‐suited for incorporating the uncertainties intrinsic to anatomy education in the areas of (1) human variations, (2) healthcare practice, (3) diversity and social justice, (4) student support, and (5) student learning. Practical recommendations for a considered approach to working alongside AI in the contemporary (and future) anatomy education learning environment are provided, including enhanced transparency about how AI is integrated, AI developer diversity, inclusion of uncertainty and anatomical variations within deployed AI, provisions made for educator awareness of AI benefits and limitations, building in curricular “AI‐free” time, and engaging AI to extend human capacities. These recommendations serve as a guiding framework for how the clinical anatomy discipline, and anatomy educators, can work alongside AI, and develop a more nuanced and considered approach to the role of AI in healthcare education.

show abstract

“…LA Dashboards typically support and augment human cognition by offering visualizations of learning data [32]. As it is important to know how the user makes sense of the information delivered with LADs, researchers start focusing on how sensemaking occurs with such tools [20].…”

Section: Supporting Sensemaking With Ladsmentioning

confidence: 99%

Designing LADs That Promote Sensemaking: A Participatory Tool

Sadallah

Gilliot

Iksal³

et al. 2022

Lecture Notes in Computer Science

View full text Add to dashboard Cite

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

show abstract

Discovering Generative Uncertainty in Learning Analytics Dashboards

Cited by 5 publications

References 39 publications

Leveraging cultural forms in human‐centred learning analytics design

Leveraging cultural forms in human‐centred learning analytics design

Artificial intelligence and clinical anatomical education: Promises and perils

Designing LADs That Promote Sensemaking: A Participatory Tool

Contact Info

Product

Resources

About